Nephrotic syndrome (NS) is a clinical syndrome of massive proteinuria caused by abnormal glomerular permeability. This proteinuria is accompanied by increased risk of infection, venous thromboembolism, and progressive loss of renal function. Morbidity also results from side effects of nonspecific immunosuppression medications used to treat this disease. The major histologic classifications of primary NS affecting children are minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS). It is challenging to provide targeted, individualized care for people at increased risk of, or currently affected by, NS. One strategy to meet this challenge is to more fully understand the genomic underpinnings of NS. This research team is studying a subset of 450 patients of all ages with incident NS recruited into two prospective observational cohorts at the time of renal biopsy. The investigators will first determine the prevalence of variants across the allele frequency spectrum for 20 genes known to cause monogenic forms of steroid-resistant NS (SRNS) and for which genotype-phenotype correlations have been observed previously. The association with clinical outcomes such as age of onset, remission of proteinuria, and decline of renal function will be determined for patients with rare variants in these genes (minor allele frequency <0.5%). The impact on SRNS outcomes from heterozygous rare variants in recessive SRNS genes or rare variants of unknown significance will also be studied, as well as possible contributions from less rare variants (0.5-1%). In addition to characterizing the clinical impact o variants in known SRNS genes, the discovery of novel genes or non-coding, regulatory genomic elements associated with NS will also be sought using an expression quantitative trait loci (eQTL) study. As opposed to a traditional genome-wide association study, the outcome for this eQTL study will be gene expression from the kidney biopsies of NS subjects. Using gene expression as an intermediate endophenotype improves power to detect significant associations and will also directly illuminate biologic pathways that would not have been detected otherwise. Finally, the investigator will continue to work with his collaborators in computational genetics to develop novel, genome-wide methods to identify genes under strong negative selection and to predict the functional impact of variants discovered in sequencing or integrative genomics studies of NS. This will be achieved by integrating genomic and functional characteristics from diverse high quality comparative genomics, population genetics, and disease specific datasets. Throughout this project, the applicant will acquire expertise in conducting integrative genomics research through these analyses and via formal coursework in bioinformatics programming, systems biology, and advanced statistical genetics. Altogether, integrating genomic variants with prospectively collected gene expression, histologic, biochemical, and clinical data will maximize ability to derive mechanistic insight about NS pathogenesis, identify novel biomarkers of risk, therapeutic response, or disease progression, and guide targeted therapeutic development strategies.